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http://lucene1.neuinfo.org/nif_resource/monthly_results/current/

An automatic pipeline based on an algorithm that identifies new resources in publications every month to assist the efficiency of NIF curators. The pipeline is also able to find the last time the resource's webpage was updated and whether the URL is still valid. This can assist the curator in knowing which resources need attention. Additionally, the pipeline identifies publications that reference existing NIF Registry resources as this is also of interest. These mentions are available through the Data Federation version of the NIF Registry, http://neuinfo.org/nif/nifgwt.html?query=nlx_144509 The RDF is based on an algorithm on how related it is to neuroscience. (hits of neuroscience related terms). Each potential resource gets assigned a score (based on how related it is to neuroscience) and the resources are then ranked and a list is generated.

Proper citation: NIF Registry Automated Crawl Data (RRID:SCR_012862) Copy   

•   Source: SciCrunch Registry
  

https://www.ohsu.edu/custom/library/digital-collections/projectionmap

Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.

Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) Copy   

•   Source: SciCrunch Registry
  

https://abcdstudy.org

Long-term study of brain development and child health in the United States. The study tracks subjects' biological and behavioral development through adolescence into young adulthood to determine how childhood experiences (such as sports, videogames, social media, unhealthy sleep patterns, and smoking) interact with each other and with a child’s changing biology to affect brain development and social, behavioral, academic, health, and other outcomes.

Proper citation: ABCD Study (RRID:SCR_015769) Copy   

•   Source: SciCrunch Registry
  

https://doi.org/10.17605/OSF.IO/WDR78

Open source resource of manually curated and expert reviewed infant brain segmentations hosted on OpenNeuro.org. and OSF.io. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1–9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.

Proper citation: Baby Open Brains (RRID:SCR_027836) Copy   

•   Source: SciCrunch Registry
  

https://painseq.shinyapps.io/harmonized_painseq_v1/

Harmonized cell atlases using sc/snRNA-seq data obtained from dorsal root ganglia and trigeminal ganglio mammalian datasets.

Proper citation: Harmonized DRG and TG Reference Atlas (RRID:SCR_025720) Copy   

•   Source: SciCrunch Registry
  

https://gseapy.readthedocs.io/en/latest/

Software Python package for performing gene set enrichment analysis. Used for characterizing gene expression changes by analysis of large single-cell datasets.

Proper citation: GSEApy (RRID:SCR_025803) Copy   

•   Source: SciCrunch Registry
  

https://github.com/SciCrunch/Antibody-Watch

Text mining antibody specificity from literature. Helps researchers identify potential problems with antibody specificity. By mining the scientific literature and linking findings to Research Resource Identifiers (RRIDs), it provides alerts on antibodies that may yield unreliable results, supporting reproducibility in biomedical research.

Proper citation: Antibody Watch (RRID:SCR_027424) Copy   

•   Source: SciCrunch Registry
  

https://github.com/smorabit/hdWGCNA

Software R package for performing weighted gene co-expression network analysis in high dimensional transcriptomics data such as single-cell RNA-seq or spatial transcriptomics.

Proper citation: hdWGCNA (RRID:SCR_027496) Copy   

•   Source: SciCrunch Registry
  

https://github.com/compbiolabucf/omicsGAN

Software generative adversarial network to integrate two omics data and their interaction network to generate one synthetic data corresponding to each omics profile that can result in better phenotype prediction. Used to capture information from interaction network as well as two omics datasets and fuse them to generate synthetic data with better predictive signals.

Proper citation: OmicsGAN (RRID:SCR_022976) Copy   

•   Source: SciCrunch Registry
  

https://app.dictyexpress.org/

Interactive web application for exploring Dictyostelium gene expression. Provides curated bulk RNA-seq developmental time courses and a developmental single-cell RNA-seq time course of wild-type AX4 and cAMP-signalling mutants. Coordinated modules (expression time courses, differential expression, hierarchical clustering, Gene Ontology enrichment and an interactive UMAP workspace) share one gene selection, and analysis sessions can be bookmarked and exported.

Proper citation: dictyExpress (RRID:SCR_029091) Copy   

•   Source: SciCrunch Registry
  

http://www.drugabuseresearchtraining.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on November 07, 2012. Decemeber 15, 2011 - Thank you for your interest in DrugAbuseResearchTraining.org. The site, courses, and resources are no longer available. Please send an email to inquiry (at) md-inc.com if you would like to be notified if the site or courses become available again. Introduction to Clinical Drug and Substance Abuse Research Methods is an online training program intended to introduce clinicians and substance abuse professionals to basic clinical research methods. The program is divided into four modules. Each module covers an entire topic and includes self-assessment questions, references, and online resources: * The Neurobiology of Drug Addiction * Biostatistics for Drug and Substance Abuse Research * Evaluating Drug and Substance Abuse Programs * Designing and Managing Drug and Substance Abuse Clinical Trials The learning objectives of this program are to help you: * Evaluate the benefits of alternative investigative approaches for answering important questions in drug abuse evaluation and treatment. * Define the proper levels of measurement and appropriate statistical methods for a clinical study. * Address common problems in data collection and analysis. * Anticipate key human subjects and ethical issues that arise in drug abuse studies. * Interpret findings from the drug abuse research literature and prepare a clinical research proposal. * Prepare research findings for internal distribution or publication in the peer reviewed literature. * Recognize drug addiction as a cyclical, chronic disease. * Understand and describe the brain circuits that are affected by addicting drugs, and explain to others the effects of major classes of addicting drugs on brain neurotransmitters. * Utilize new pharmacologic treatments to manage persons with drug addiction. Physicians can earn AMA PRA Category 1 Credit and purchase a high resolution printable electronic CME certificate(view sample); non-physicians can purchase high resolution printable electronic certificate of course participation that references AMA PRA Category 1 credit (view sample). This program does not offer printed certificates.

Proper citation: Online Education for the International Research Community: AboutIntroduction to Clinical Drug and Substance Abuse Research Methods (RRID:SCR_000802) Copy   

•   Source: SciCrunch Registry
  

http://www.drugabuse.gov/about/organization/CEWG/

A network composed of researchers from major metropolitan areas of the United States and selected foreign countries which meet semiannually to discuss the current epidemiology of drug abuse. The primary mission of the Work Group is to provide ongoing community-level surveillance of drug abuse through analysis of quantitative and qualitative research data. Through this program the CEWG provides current descriptive and analytical information regarding the nature and patterns of drug abuse, emerging trends, characteristics of vulnerable populations and social and health consequences. Reports Reports are available from the biannual meetings at which the network members discuss current and emerging problems of substance abuse. At the meetings, CEWG members present data on drug abuse from a variety of city, State, Federal, and other sources. These data are enhanced with information gathered through ethnographic research, focus groups, interviews, and other qualitative methods. This integration of quantitative with qualitative data provides invaluable insight into emerging drug use trends. Book In 1998, the National Institute on Drug Abuse (NIDA) published the first edition of Assessing Drug Abuse Within and Across Communities: Community Epidemiology Surveillance Networks on Drug Abuse to share information on establishing drug abuse epidemiology networks at community and State levels. Its purpose is to provide guidelines for establishing epidemiology networks to monitor and assess drug abuse patterns and trends and emerging drug problems at community and State levels to provide a foundation of information for public health response. The second edition differs from the first in format. For each data source, there is a description of the source and database, followed by guidelines on how to access the data (including Web sites) and what to request, and examples of how the data have been used by epidemiology work groups or Federal agencies. NIDA hopes that this revised guide is helpful to agencies, organizations, and researchers that are involved in or wish to establish epidemiology networks in their communities or States.

Proper citation: Community Epidemiology Work Group (RRID:SCR_002751) Copy   

•   Source: SciCrunch Registry
  

http://neuinfo.org

Framework for identifying, locating, relating, accessing, integrating, and analyzing information from neuroscience research. Users can search for and add neuroscience-related resources at NIF portal and receive and RRID to track and cite resources within scientific manuscripts.

Proper citation: Neuroscience Information Framework (RRID:SCR_002894) Copy   

•   Source: SciCrunch Registry
  

http://trans.nih.gov/bmap/resources/resources.htm

As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com

Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy   

•   Source: SciCrunch Registry
  

https://neurobiobank.nih.gov/

National resource for investigators utilizing human post-mortem brain tissue and related biospecimens for their research to understand conditions of the nervous system. Federated network of brain and tissue repositories in the United States that collects, evaluates, stores, and makes available to researchers, brain and other tissues in a way that is consistent with the highest ethical and research standards. The NeuroBioBank ensures protection of the privacy and wishes of donors. Provides information to the public about the need for tissue donation and how to register as a donor.

Proper citation: NIH NeuroBioBank (RRID:SCR_003131) Copy   

•   Source: SciCrunch Registry
  

https://datashare.nida.nih.gov

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

Proper citation: NIDA Data Share (RRID:SCR_002002) Copy   

•   Source: SciCrunch Registry
  

http://antibodyregistry.org/

Public registry of antibodies with unique identifiers for commercial and non-commercial antibody reagents to give researchers a way to universally identify antibodies used in publications. The registry contains antibody product information organized according to genes, species, reagent types (antibodies, recombinant proteins, ELISA, siRNA, cDNA clones). Data is provided in many formats so that authors of biological papers, text mining tools and funding agencies can quickly and accurately identify the antibody reagents they and their colleagues used. The Antibody Registry allows any user to submit a new antibody or set of antibodies to the registry via a web form, or via a spreadsheet upload.

Proper citation: Antibody Registry (RRID:SCR_006397) Copy   

•   Source: SciCrunch Registry
  

https://www.phenxtoolkit.org/

Set of measures intended for use in large-scale genomic studies. Facilitate replication and validation across studies. Includes links to standards and resources in effort to facilitate data harmonization to legacy data. Measurement protocols that address wide range of research domains. Information about each protocol to ensure consistent data collection.Collections of protocols that add depth to Toolkit in specific areas.Tools to help investigators implement measurement protocols.

Proper citation: Phenotypes and eXposures Toolkit (RRID:SCR_006532) Copy   

•   Source: SciCrunch Registry
  

http://cancercontrol.cancer.gov/tcrb/tturc/

A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.

Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy   

•   Source: SciCrunch Registry
  

http://www.webgestalt.org/

Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.

Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy   

•   Source: SciCrunch Registry